Digital images can express a poor reproduction of a target scene due to various limitations in the sensing technology. Whether captured with a digital camera directly, by scanning a photograph or by some other method, sensor limitations can affect image quality. Aperture, exposure time, lighting conditions, sensor sensitivity and calibration and other factors can affect image characteristics. These variables can affect image sensing and recording such that the recorded image differs significantly from an observer's perception of the actual image target scene. These variations may comprise under-exposure, over-exposure, flatness, bi-modality and others.
An individual's perception of image quality and the accuracy with which an image reproduces it's target scene is also influenced by the subjective preferences of the viewer. While some viewer preferences can be modeled by mathematical functions, other preferences are not easily represented mathematically.
Under-exposed or over-exposed images can be adjusted by reshaping the luminance channel histogram. Generally, peaks and valleys are normalized to obtain a more constant luminance level throughout the image. However, in some scenarios, this technique can produce images that are more objectionable to a viewer than the un-adjusted image.
Human perception of lightness has been well studied. These studies are well documented in works such as: Adelson, E. H. (1993). “Perceptual Organization and the Judgment of Brightness.” Science 262(24): 2042–2044; Adelson, E. H. (2000). Lightness Perception and Lightness Illusions. The New Cognitive Neurosciences. M. Gazzaniga. Cambridge, Mass., MIT Press: 339–351; Gilchrist (2002), A. Unified Luminance Anchoring Theory. 2002; and Pentland, E. H. A. a. A. P. (1996). The perception of shading and reflectance. Perception as Bayesian Inference. D. K. a. W. Richards. New York, Cambridge University Press: 409–423.
However, the human preference for various tone renderings of natural images is not well understood. A model for the prediction of human preferences for tone parameters is not presently available. Accordingly, automatic enhancement of image defects to more closely conform to viewer preferences can be difficult or impossible to perform using known techniques.